Networks and the Macroeconomy: An Empirical Exploration

Daron  Acemoglu; Ufuk  Akcigit; William R. Kerr

Chapter | NBER Macroeconomics Annual 2015, Vol. 30 | 2016

Networks and the Macroeconomy: An Empirical Exploration

by Daron Acemoglu, Ufuk Akcigit and William R. Kerr

Abstract

The propagation of macroeconomic shocks through input-output and geographic networks can be a powerful driver of macroeconomic fluctuations. We first exposit that in the presence of Cobb-Douglas production functions and consumer preferences, there is a specific pattern of economic transmission whereby demand-side shocks propagate upstream (to input-supplying industries), and supply-side shocks propagate downstream (to customer industries), and that there is a tight relationship between the direct impact of a shock and the magnitudes of the downstream and the upstream indirect effects. We then investigate the short-run propagation of four different types of industry-level shocks: two demand-side ones (the exogenous component of the variation in industry imports from China and changes in federal spending) and two supply-side ones (TFP shocks and variation in knowledge/ideas coming from foreign patenting). In each case, we find substantial propagation of these shocks through the input-output network, with a pattern broadly consistent with theory. Quantitatively, the network-based propagation is larger than the direct effects of the shocks. We also show quantitatively large effects from the geographic network, capturing the fact that the local propagation of a shock to an industry will fall more heavily on other industries that tend to collocate with it across local markets. Our results suggest that the transmission of various different types of shocks through economic networks and industry interlinkages could have first-order implications for the macroeconomy.

Keywords: economic fluctuations; geographic collocation; input-output linkages; networks; propagation; shocks; Networks; Fluctuation; System Shocks; Macroeconomics;

Format: Print

Read Now

Citation:

Acemoglu, Daron, Ufuk Akcigit, and William R. Kerr. "Networks and the Macroeconomy: An Empirical Exploration." In NBER Macroeconomics Annual 2015, Vol. 30, edited by Martin Eichenbaum and Jonathan Parker, 273–335. Chicago, IL: University of Chicago Press, 2016.

This primer is meant to be a field guide to the late 2010s' surge in business use of "Artificial Intelligence" (AI), or enterprise software based in machine learning. First, it provides an overview of the key trends - digitization, connectivity, the continuation of Moore's law, and advancements in machine learning algorithms - which led to the inflection point in adoption of AI. Then, the primer describes the range of use cases of state-of-the-art enterprise AI organized in a taxonomy designed to build generalized understanding of the types of work to which AI can be applied. This knowledge is useful not only to managers looking to best leverage the technology but to those working to manage resulting organizational change and prepare the workforce for transitions into complementary tasks. Finally, key issues and implications of AI adoption are also discussed.

Tech clusters like Silicon Valley play a central role for modern innovation, business competitiveness, and economic performance. This paper reviews what constitutes a tech cluster, how they function internally, and the degree to which policy makers can purposefully foster them. We describe the growing influence of advanced technologies for businesses outside of traditional tech fields, the strains and backlash that tech clusters are experiencing, and emerging research questions for theory and empirical work.

Faculty & Research

Networks and the Macroeconomy: An Empirical Exploration

Abstract

Citation:

About the Author

More from the Author